Concurrent AURKA and MYCN Gene Amplifications Are Harbingers of Lethal TreatmentRelated Neuroendocrine Prostate Cancer
Bibliographic record
Abstract
Neuroendocrine prostate cancer (NEPC), also referred to as anaplastic prostate cancer, is a lethal tumor that most commonly arises in late stages of prostate adenocarcinoma (PCA) with predilection to metastasize to visceral organs. In the current study, we explore for evidence that Aurora kinase A (AURKA) and N-myc (MYCN) gene abnormalities are harbingers of treatment-related NEPC (t-NEPC). We studied primary prostate tissue from 15 hormone naïve PCAs, 51 castration-resistant prostate cancers, and 15 metastatic tumors from 72 patients at different stages of disease progression to t-NEPC, some with multiple specimens. Histologic evaluation, immunohistochemistry, and fluorescence in situ hybridization were performed and correlated with clinical variables. AURKA amplification was identified in overall 65% of PCAs (hormone naïve and treated) from patients that developed t-NEPC and in 86% of metastases. Concurrent amplification of MYCN was present in 70% of primary PCAs, 69% of treated PCAs, and 83% of metastases. In contrast, in an unselected PCA cohort, AURKA and MYCN amplifications were identified in only 5% of 169 cases. When metastatic t-NEPC was compared to primary PCA from the same patients, there was 100% concordance of ERG rearrangement, 100% concordance of AURKA amplification, and 60% concordance of MYCN amplification. In tumors with mixed features, there was also 100% concordance of ERG rearrangement and 94% concordance of AURKA and MYCN co-amplification between areas of NEPC and adenocarcinoma. AURKA and MYCN amplifications may be prognostic and predictive biomarkers, as they are harbingers of tumors at risk of progressing to t-NEPC after hormonal therapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".